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Recent advances in diffusion models have led to impressive image generation capabilities, but aligning these models with human preferences remains challenging. Reward-based fine-tuning using models trained on human feedback improves…

Computer Vision and Pattern Recognition · Computer Science 2025-05-29 Dmitrii Sorokin , Maksim Nakhodnov , Andrey Kuznetsov , Aibek Alanov

This paper presents a method to reconstruct high-quality textured 3D models from both multi-view and single-view images. The reconstruction is posed as an adaptation problem and is done progressively where in the first stage, we focus on…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Aysegul Dundar , Jun Gao , Andrew Tao , Bryan Catanzaro

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

The rapid adoption of text-to-image diffusion models in society underscores an urgent need to address their biases. Without interventions, these biases could propagate a skewed worldview and restrict opportunities for minority groups. In…

Machine Learning · Computer Science 2024-03-18 Xudong Shen , Chao Du , Tianyu Pang , Min Lin , Yongkang Wong , Mohan Kankanhalli

Image retouching aims to enhance the visual quality of photos. Considering the different aesthetic preferences of users, the target of retouching is subjective. However, current retouching methods mostly adopt deterministic models, which…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Zheng-Peng Duan , Jiawei zhang , Zheng Lin , Xin Jin , Dongqing Zou , Chunle Guo , Chongyi Li

Text-to-image diffusion models have revolutionized image synthesis and editing, but precise control over stylistic attributes remains a challenge, often causing unintended content modifications. We propose an approach for fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Max Reimann , Benito Buchheim , Jürgen Döllner

Large-scale Text-to-Image (T2I) models have rapidly gained prominence across creative fields, generating visually compelling outputs from textual prompts. However, controlling these models to ensure consistent style remains challenging,…

Computer Vision and Pattern Recognition · Computer Science 2024-01-12 Amir Hertz , Andrey Voynov , Shlomi Fruchter , Daniel Cohen-Or

Video virtual try-on aims to seamlessly replace the clothing of a person in a source video with a target garment. Despite significant progress in this field, existing approaches still struggle to maintain continuity and reproduce garment…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Jinjuan Wang , Wenzhang Sun , Ming Li , Yun Zheng , Fanyao Li , Zhulin Tao , Donglin Di , Hao Li , Wei Chen , Xianglin Huang

We propose a novel visual SLAM method that integrates text objects tightly by treating them as semantic features via fully exploring their geometric and semantic prior. The text object is modeled as a texture-rich planar patch whose…

Computer Vision and Pattern Recognition · Computer Science 2023-07-04 Boying Li , Danping Zou , Yuan Huang , Xinghan Niu , Ling Pei , Wenxian Yu

Large scale text-guided diffusion models have garnered significant attention due to their ability to synthesize diverse images that convey complex visual concepts. This generative power has more recently been leveraged to perform text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-09-20 Etai Sella , Gal Fiebelman , Peter Hedman , Hadar Averbuch-Elor

Text-driven image generation using diffusion models has recently gained significant attention. To enable more flexible image manipulation and editing, recent research has expanded from single image generation to transparent layer generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Junjia Huang , Pengxiang Yan , Jinhang Cai , Jiyang Liu , Zhao Wang , Yitong Wang , Xinglong Wu , Guanbin Li

Current texture synthesis methods, which generate textures from fixed viewpoints, suffer from inconsistencies due to the lack of global context and geometric understanding. Meanwhile, recent advancements in video generation models have…

Graphics · Computer Science 2025-06-27 Donggoo Kang , Jangyeong Kim , Dasol Jeong , Junyoung Choi , Jeonga Wi , Hyunmin Lee , Joonho Gwon , Joonki Paik

This paper presents TexRO, a novel method for generating delicate textures of a known 3D mesh by optimizing its UV texture. The key contributions are two-fold. We propose an optimal viewpoint selection strategy, that finds the most…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Jinbo Wu , Xing Liu , Chenming Wu , Xiaobo Gao , Jialun Liu , Xinqi Liu , Chen Zhao , Haocheng Feng , Errui Ding , Jingdong Wang

Subject-driven image inpainting has recently gained prominence in image editing with the rapid advancement of diffusion models. Beyond image guidance, recent studies have explored incorporating text guidance to achieve identity-preserved…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Yicheng Yang , Pengxiang Li , Lu Zhang , Liqian Ma , Ping Hu , Siyu Du , Yunzhi Zhuge , Xu Jia , Huchuan Lu

Previous text-to-image synthesis algorithms typically use explicit textual instructions to generate/manipulate images accurately, but they have difficulty adapting to guidance in the form of coarsely matched texts. In this work, we attempt…

Computer Vision and Pattern Recognition · Computer Science 2023-09-12 Mengyao Cui , Zhe Zhu , Shao-Ping Lu , Yulu Yang

Text-to-image diffusion models have emerged as powerful tools for high-quality image generation and editing. Many existing approaches rely on text prompts as editing guidance. However, these methods are constrained by the need for manual…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Yuanyuan Chang , Yinghua Yao , Tao Qin , Mengmeng Wang , Ivor Tsang , Guang Dai

Text-to-image (T2I) diffusion models, with their impressive generative capabilities, have been adopted for image editing tasks, demonstrating remarkable efficacy. However, due to attention leakage and collision between the cross-attention…

Computer Vision and Pattern Recognition · Computer Science 2025-05-01 Xingxi Yin , Zhi Li , Jingfeng Zhang , Chenglin Li , Yin Zhang

Recently, the application of modern diffusion-based text-to-image generation models for creating artistic fonts, traditionally the domain of professional designers, has garnered significant interest. Diverging from the majority of existing…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Xinzhi Mu , Li Chen , Bohan Chen , Shuyang Gu , Jianmin Bao , Dong Chen , Ji Li , Yuhui Yuan

Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly complex visual concepts. However, a pivotal challenge in…

Computer Vision and Pattern Recognition · Computer Science 2022-11-24 Narek Tumanyan , Michal Geyer , Shai Bagon , Tali Dekel

As large-scale text-to-image generation models have made remarkable progress in the field of text-to-image generation, many fine-tuning methods have been proposed. However, these models often struggle with novel objects, especially with…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Jianxiang Lu , Cong Xie , Hui Guo